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A Study of Prediction Based on Regression Analysis for Real-World Co2 Emissions with Light-Duty Diesel Vehicles

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Abstract

The objective in present study is to develop a regression analysis model to estimate real-world CO2 emissions of light-duty diesel vehicles considering domestic road conditions. For regression analysis variables, OBD data such as vehicle speed, acceleration, engine speed (rpm), and engine power were used. Regression analysis results were compared with CO2 emissions measured using PEMS on the test routes of the real driving emissions-light duty vehicles (RDE-LDV). In results, the vehicle speed and air/fuel data from the OBD signals maintained a linear relationship with the GPS and exhaust gas flowmeter-based vehicle speed and exhaust flow data. All determination coefficients were ≥0.99, indicating that the OBD data provided by the test vehicle in this study exhibited strong reliability. To investigate the accuracy of the regression equation estimated using the trip variables of the OBD data, the driving variables were substituted into the equation to obtain CO2 estimations and the real CO2 emissions measured using PEMS were compared. A strong linear relationship was observed between the regression equation-based CO2 estimations and real CO2 measurements. The determination coefficient was approximately 0.93, supporting the reliability of the estimation results.

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Abbreviations

DOC:

Diesel Oxidation Catalyst

DPF:

Diesel Particulate Filter

GHG:

Greenhouse Gas

LDV:

Light-Duty Vehicles

NEDC:

New European Driving Cycle

OBD:

On-board Diagnostics

PEMS:

Portable Emissions Measurement System

RDE:

Real Driving Emissions

SCR:

Selective Catalytic Reduction

WLTC:

World-wide harmonized Light-duty vehicles Test Cycle

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Acknowledgement

This research was supported by the National Institute of Environmental Research (NIER), the National Research Foundation of Korea (NRF-2019R1I1A3A01062771), and the Korea Evaluation Institute of Industrial Technology (Keit, 20002762).

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Authors and Affiliations

  1. Department of Automotive Engineering, Korea National University of Transportation, Chungju, 27469, Korea

    Junepyo Cha, Hyoungwook Lee & Mun Soo Chon

  2. Transport Pollution Research Center, National Institute of Environmental Research (NIER), Hwangyong-ro 42, Seogu, Incheon, 22689, Korea

    Junhong Park

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  1. Junepyo Cha
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  3. Hyoungwook Lee
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  4. Mun Soo Chon
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Correspondence to Mun Soo Chon.

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Cha, J., Park, J., Lee, H. et al. A Study of Prediction Based on Regression Analysis for Real-World Co2 Emissions with Light-Duty Diesel Vehicles. Int.J Automot. Technol. 22, 569–577 (2021). https://doi.org/10.1007/s12239-021-0053-z

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